code: def test_cross_validation(shutdown_only):
      register_ray()
      iris = load_iris()
      clf = SVC(kernel="linear", C=1, random_state=0)
      with joblib.parallel_backend("ray", n_jobs=5):
          accuracy = cross_val_score(clf, iris.data, iris.target, cv=5)
      assert len(accuracy) == 5
      for result in accuracy:
          assert result > 0.95
  
imports: import joblib
  import sys
  import time
  import os
  import pytest
  from unittest import mock
  import pickle
  import numpy
  from sklearn.datasets import load_digits, load_iris
  from sklearn.model_selection import RandomizedSearchCV
  from sklearn.ensemble import ExtraTreesClassifier
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.kernel_approximation import Nystroem
  from sklearn.kernel_approximation import RBFSampler
  from sklearn.pipeline import make_pipeline
  from sklearn.svm import LinearSVC, SVC
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.neural_network import MLPClassifier
  from sklearn.model_selection import cross_val_score
  from ray.util.joblib import register_ray
  import ray
label_desc: Use image node_id 6 for calling a global function with example usage: test_cross_validation(shutdown_only) without return types